| In the last decades, nanotechnology has built great expectations because of its unique capabilities in engineering materials with tailored properties. Exhibiting enhanced physical and chemical properties at length scale on the order of 1{10 nm, nanostructured materials have contributed more than ever, ranging from energy generation, storage, and conversion with applications in lithium ion battery electrodes, solid oxide fuel cell electrodes, thermoelectric heat recovery, and perovoskite solar cells. Recent findings suggest that the composition, structure, and properties of multifunctional materials are governed at nanoscale and are substantially different than of the bulk properties. While the chemical and phase composition of these materials can be mapped with atomic and sub-atomic resolution, the structural mappings do not provide significant information on nanoscale physical properties. Indeed, there is still a lack of techniques that can effectively probe local phenomena and link the nanoscale properties to bulk performance and microstructure of material.;Atomic Force Microscope (AFM) is a versatile tool for imaging, measurements, and manipulation of matter with nanometer spatial resolution and picometer detection accuracy. Over the last three decades, advanced AFM modes and functionalized probes were developed and employed in magnetic and ferroelectric studies, electrochemical characterizations, viscoelastic measurements, and quantum transport imaging. Despite the tremendous improvements in AFM platforms, functionalized probes, and imaging techniques, AFM measurements are not without challenges. For instance, the signal formation mechanism is complex and consists of several contributions. The resonance-enhanced techniques used for intrinsic characterization of functional materials are prone to topography and feedback crosstalks and often results in unreliable measurements. Obtaining quantitative measurements that can directly link to the probed physical phenomena is a non-trivial job.;The first goal of this dissertation was to develop advanced excitation, detection, and data analysis techniques that can measure nonlinear phenomena, resolve topographic and feedback cross-talks, and extract intrinsic properties. A multi-harmonic dual resonance tracking technique is implemented on a commercial AFM system, nonlinear resonance-enhanced AFM responses are obtained, and the intrinsic properties are determined and visualized. The other developed technique is an open-loop sequential excitation that performs a series of single frequency lock-in measurement. Finally, a method based on acquisition of highly sampled time domain AFM signals was developed and implemented. Multivariate statistical analysis, such as principal component analysis (PCA), is performed on AFM data to enhance signal-to-noise ratio and statistically relevant modes of the data. The first few modes of the data contain relevant information while the rest of the modes only contain noise. The low-rank reconstructed data further analyzed via wavelet-based time-frequency analysis as well physics-based methods and intrinsic properties are revealed.;The second part of the dissertation deals with novel AFM imaging modes on the foundation of excitation and detection schemes explained in the previous part. Currently, the state-of-the-art AFM imaging modes used to characterize ferroelectric and ionic and material systems are known as piezoresponse force microscopy (PFM) and electrochemical strain microscopy (ESM). PFM and ESM are identical in implementation and are based on application of an alternating bias to the probe tip in contact with the material and measurement of the induced dynamic strain by AFM cantilever motion. It is virtually impossible to distinguish the ionic, ferroelectric, and electrostatic contributions while scanning a material. Scanning thermo-ionic microscopy (STIM) was proposed and developed by measuring the dynamic deflection induced by simultaneous oscillations of local hydrostatic stress and temperature at the probe tip. The probe tip is not charged and the signal formation originates from ionic diffusion and does not consist of piezoelectric and electrostatic effects. The signal formation mechanism was examined on an ionically conductive sample Sm-doped ceria and not ionically conductive PTFE sample. STIM was implemented using two excitation methods: resistive heating and photo-thermal excitations. Having local control on nanoscale heat transfer, a method was introduced to quantitatively measure the thermal conductivity of the sample through a combination of experimental and numerical calibration studies. Thermal conductivity can be measured with good accuracy and high spatial resolution. The method was applied on a three-phase thermoelectric sample and is a powerful tool to optimize the conversion efficiency of thermoelectric materials... |
